Kindbridge Behavioral Health Signs of Sports Betting Addiction

Signs of Sports Betting Addiction

This blog outlines the latest insights and information on sports betting, including signs of sports betting addiction and where to seek help.

What is sports betting?

Sports betting is a form of gambling where people bet on sporting events. The majority of bets are on traditional professional sports such as soccer, horse racing, boxing, basketball, baseball, hockey, rugby, cricket, and cycling. However, sports betting can also extend to non-sporting events such as reality TV, political elections, and entertainment awards.

While some countries and regions prohibit sports betting, in most parts of the world, sports betting is considered a legal form of gambling and is licensed and regulated by special commissions. In the United States, sports betting was lifted by the U. S. Supreme Court in 2018. Since then, many states have legalized sports betting.

Sports bettors place bets either legally through brick-and-mortar or online bookmakers (also known as betting agencies or sportsbooks) or illegally through private companies. Bookmakers offer odds on sporting events, and there are many types of bets. Here are some of the most popular ones:

Money line bets require the selected team to win the game outright.
Spread betting is based on the accuracy of the bet, rather than a simple win or loss.
Over-under bets are made based on the combined score of both teams.
Proposition bets are bets on certain elements of the match, regardless of the final score.
An accumulator or parry involves multiple bets that pay out a larger amount if all predictions are correct.

Sports betting has also become popular in esports (competitive online video games). Esports betting is more or less the same as traditional sports betting, but when betting on esports matches, players can choose between cash-based or skin-based websites. During the Covid-19 pandemic, with almost all real-life sporting events canceled, the viewership of esports increased dramatically. The sports betting industry quickly turned to esports, and many of the traditional sports bettors also switched to esports.

The surge in online sports gambling has made it easier than ever for players to place bets from the comfort of their homes. But this 24/7 access has led to a rise in sports betting addiction.

Sports betting statistics

In 2017 US surveys, 45%of respondents had bet at least once in their lives, but only 4%said they were doing regularly. (Statista, 2018)
According to the survey, 45 % of online gambling worldwide is due to sports betting. The second place was 24 % for casino online gambling. (Statista, 2018)
20%of American men answered that they were participating in sports betting, while 7%of women. (Morning consultant, 2020)
According to a 2020 survey, the age group was 30-44 years old (22 %) in the United States. (Statista, 2020)
In a 2017 survey for adults in the United States who participated in sports betting, we asked what I like about sports betting: Making sports more interesting (45 %), enjoying the side games while watching the main events (45 %). 38 %), enjoy betting (34 %) as a means of competing with friends and colleagues, and enjoy excitement and thrills (29 %). (Statista, 2017)
Sports that was the highest interest in sports betting in the United States in 2019: US Football League (61 %) National Basketball Association (58 %) Major League (53 %) Boxing (42 %) Horse racing (35 %) Hockey League (32) %) US Stock Car Auto Race Association (28 %) ESPORTS (23 %) Major League Soccer (21 %) Women's basketball association (16 %). (Statista, 2019)
The total income of Sportsbetting in the United States is expected to grow to $ 2. 5 billion in 2021, and in 2025 this figure will grow to $ 8 billion. (Statista, 2021)

Signs and symptoms of sports betting addiction

Most people who participate in sports betting are recreation, but some are addicted like drugs. Here are some general signs and symptoms that may have become incapacitated with sports betting:

Always think about betting and plan the next bed method and timing.
In order to get the same uplifting, you need to bet more.
I try to suppress, try to reduce, and try to stop, but it doesn't work.
When you are not betting, you feel sad, frustration, calmness, anxiety, and in extreme cases you become aggressive or violent.
Escape from problems, bet to relieve stress, anxiety, and depression.
Bet more to make up for losing, but in most cases, you lose more money.
Love the opportunity for education and career for the time spent and energy spent on betting.
I will keep a distance from friends, family and colleagues.
Dye theft and fraud to support habits.
Lies to hide the degree of problem.
B.
Since he lost a lot of money by betting, he asked others for financial assistance.

If you are aware of the above signs or symptoms, or if your loved one has shown some of these actions, it is time to ask for the help of an expert. Take the gambling addiction test.

Dangers of sports betting

Some people do sports betting without noticeable dangerous acts, while others become dangerous. Leaving sports betting poisoning without treatment can have a lot of adverse effects in social, psychological and physical.

Human relationships, bankruptcy, debt, financial problems, bankruptcy, work problems and unemployment, stress, anxiety, depression, anorexia, gastrointestinal disorders, etc. In extreme cases, suicide desires and attempted suicide may be connected.

How to get help for sports betting addiction

If you are worried about sports betting, or if you think that others may be gambling, Kind Bridge will help you.

We believe that the treatment of sports betting addiction is not only to deal with betting, but also to support mental health and happiness in general. The excellent therapist of the center will create a recovery plan that suits each customer, and will help customers regain control and put their lives on track.

Determinants of problem sports betting among college students: moderating roles of betting frequency and impulsive betting tendency

In consideration of the risk of betting problems and an increase in the rate of incidence in young people, the purpose of this study is to understand what it affects the behavior of university students using a planned behavior theory (TPB). Ta.

Methods

An organizatio n-based crossing research was conducted. The data was collected from 311 university students in the United States using a survey form, and mainly analyzed using the minimum two-square structural equation modeling (PLS-SEM) method, and investigated the relationship between research variables. In addition, a mult i-group SEM analysis was implemented to investigate the adjustment of the frequency of betting and impulsive betting trends related to sports betting. I lost a lot of money by betting, so I asked others for financial assistance.

Results

If you are aware of the above signs or symptoms, or if your loved one has shown some of these actions, it is time to ask for the help of an expert. Take the gambling addiction test.

Conclusion

Introduction

If you are worried about sports betting, or if you think that others may be gambling, Kind Bridge will help you.

We believe that the treatment of sports betting addiction is not only to deal with betting, but also to support mental health and happiness in general. The excellent therapist of the center will create a recovery plan that suits each customer, and customers will regain control and help you put your life on track.

Sports betting and problem betting behavior

An organizatio n-based crossing research was conducted. The data was collected from 311 university students in the United States using a survey form, and mainly analyzed using the minimum two-square structural equation modeling (PLS-SEM) method, and investigated the relationship between research variables. In addition, a mult i-group SEM analysis was implemented to investigate the adjustment of the frequency of betting and impulsive betting trends related to sports betting. Since he lost a lot of money by betting, he asked others for financial assistance.

Theory of planned behavior and sports gambling behavior

If you are aware of the above signs or symptoms, or if your loved one has shown some of these actions, it is time to ask for the help of an expert. Take the gambling addiction test.

If you are worried about sports betting, or if you think that others may be gambling, Kind Bridge will help you.

Study hypotheses

An organizatio n-based crossing research was conducted. The data was collected from 311 university students in the United States using a survey form, and mainly analyzed using the minimum two-square structural equation modeling method (PLS-SEM), and investigated the relationship between research variables. In addition, a mult i-group SEM analysis was implemented to investigate the adjustment of the frequency of betting and impulsive betting trends related to sports betting.

The results suggest that sports betting intention (SBI) among college students is related to attitudes toward sports betting, motivation to follow others, and subjective norms, in that order, but not to perceived behavioral control (PBC). Problem sports betting (PSB) was significantly positively correlated with SBI and negatively correlated with PBC. Furthermore, multigroup analysis revealed that betting frequency and impulsive betting tendency played a moderating role, especially in the relationship between SBI and PSB. The relationship between SBI and PSB was stronger in the low betting frequency and low impulsive betting groups than in the high betting frequency and high impulsive betting groups.

Hypothesis 1

Overall, the importance of peer influence and attitude formation regarding sports betting was highlighted. Recognizing what influences PSB and the role of habitual and impulsive sports betting in this population is recommended for developing appropriate public health programs to reduce PSB problems.

Hypothesis 2

Given the lasting impact of problem gambling and betting on young people and the growing size of the sports gambling industry [1], it is crucial to understand what influences sports betting-related behaviors among college-aged people [1, 2, 3, 4]. In the United States, as the NBA Commissioner noted, “the expansion of legalized sports betting” is inevitable [5]. In addition, betting companies’ investment in sports as corporate sponsorship has also increased in recent decades [6, 7]. In countries where sports betting culture has been established for a long time, such as the UK, more people are experiencing sports betting and related problems. For example, the number of problem bettors is increasing, and many younger people in particular are showing signs of betting problems [8, 9, 10].

Hypothesis 3

The Planning and Behavior theory (TPB) is applied to understand the intentions and actions related to betting, to understand the behavior of the behavior and/ or ((()]. There are quite a lot of research on gambling for university students using TPB [13, 14], but not many researchers investigated the problem of sport s-related problems [6]. In this study, the subjective norm, which is one of the TPB variables, uses the two components / scale of subjective norms, including normative beliefs and motivation for compliance with others, but this is the living environment and age of university students. Considering, it is still susceptible to friends. He also examined the impulsive betting tendency of individuals and the coordinating roles of the past sports betting (that is, the frequency of betting) in the problem sports betting.

Hypothesis 4

Therefore, in this study, the factors that predict university students' sports betting behavior (such as sports betting intentions, problem sports betting behavior, etc.) are planned behavior theory [11, 12], that is, the attitude and perception of subjective norms, sports betting. It was evaluated using the contribution of action and motivation to follow others. In this study, in order to further understood university students' sports bettin g-related behaviors, TP B-based research also incorporated an extr a-volatile factor (such as impulsive sports betting tendency).

Hypothesis 5

Since the extremely important Supreme Court ruling in 2018, the United States has the authority to legalize sports betting. As a result, about tw o-thirds of the United States have approved the legalization of sports betting in some form, and about 80%of states legalize sports betting or at least legalize sports betting. I propose. For example, Ohio's bill is passed in 2021 and will be enforced in 2023 [16, 17]. As a matter of course, the number and frequency of sports betting in the United States are increasing year by year. In December 2021, 24%of Americans participated in sportsbetting, of which 12%bet on sports every week. Sports betting has grown significantly since legalization, to $ 40. 3 billion in 2018, but in 2021 it was $ 433 billion. As of May 2022, more than $ 125 billion was betting since the start of 2018. According to the National Gambling Administration Council (NCPG), sports are more likely to bet on gamblers who do not bet on sports. [18]

Hypothesis 6

Online sports bettors are also more likely to have betting problems than offline/in-person sports bettors. In fact, it is assumed that about 29% of online sports bettors have gambling problems or gambling disorders [18]. With sports betting legalized and revenues predicted to increase in the coming years, the United States is expected to see higher levels of betting problems, especially among younger (up to 35 years old) male populations [9, 18, 19]. Therefore, in order to promote healthier sports betting behavior, it is essential to understand what influences problem betting behavior among (potential) sports bettors.

The TPB is one of the most effective frameworks for understanding what influences an individual's intention to engage in a particular behavior [12]. The TPB posits that an individual’s attitudes (i. e., how people evaluate the focal behavior), subjective norms (i. e., how people perceive significant others’ evaluations of the focal behavior), and perceived behavioral control (PBC) (i. e., how people evaluate their own control over the focal behavior or how they perceive their self-efficacy for a particular behavior) determine the intention to perform a particular behavior [11, 12]. Thus, an individual is likely to have a high intention to perform a particular behavior if he or she has a positive attitude toward a particular behavior, positive social norms regarding this behavior, and a strong sense of good behavioral control regarding performing a particular behavior [12]. Similarly, a (potential) sports bettor is more likely to perform sports betting activities if the individual has a positive attitude toward sports betting, is surrounded by significant others who support sports betting, and has control over sports betting activities.

TPB has been used to understand gambling and gambling behaviors of young adults [14, 20, 21, 22, 23]. For example, WU and Tang are the most predicted of gambling, following the attitude toward gambling, based on the attitude toward gambling, based on the attitude toward gambling, but the gambling is significantly correlated with the intention and PBC. I found that [14]. Using the Australian online survey panel, Flack and Morris have discovered that subjective norms (that are, normative beliefs) are the strongest gambling decision factors compared to other TPB variables. Gambling intention was a significant predictor of gambling frequency. In the situation in Canada, ST-PIERRE and his colleagues have significantly correlated with their attitude toward gambling and PBC over gambling, but are not correlated with the subjective norms of gambling. [21] Furthermore, the gambling frequency of Better was significantly related to gambling intentions, followed by gambling attitudes, and recognized gambling problems were more commonly predicted by the PBC, followed by gambling intentions. As a whole, ST-PIERRE and his colleagues suggested the effectiveness of TPB in prediction of gambling behavior, including gambling.

Similarly, Martin et al. Found that TPB determination factors were effective forecast factors for both past gambling behavior and gambling intentions. Specifically, gambling intentions were most closely related to the subjective norms of friends and family, followed by PBC. In a similar context of casino gambling, Lee has a favorable decision on casino gambling, along with the exposure of gambling media and past gambling experience with college students' casino gambling. He discovered that it was a factor. However, in Lee studies on U. S. university students, the control of the casino gambling was not a significant proximity forecast. TPB has been used to understand the gambling and gambling behavior of young adults [14, 20, 21, 22, 23]. For example, WU and Tang are the most predicted of gambling, following the attitude toward gambling, based on the attitude toward gambling, based on the attitude toward gambling, but the gambling is significantly correlated with the intention and PBC. I found that [14]. Using the Australian online survey panel, Flack and Morris have discovered that subjective norms (that are, normative beliefs) are the strongest gambling decision factors compared to other TPB variables. Gambling intention was a significant predictor of gambling frequency. In the situation in Canada, ST-PIERRE and his colleagues have significantly correlated with their attitude toward gambling and PBC over gambling, but are not correlated with the subjective norms of gambling. [21] Furthermore, the gambling frequency of Better was significantly related to gambling intentions, followed by gambling attitudes, and recognized gambling problems were more commonly predicted by the PBC, followed by gambling intentions. As a whole, ST-PIERRE and his colleagues suggested the effectiveness of TPB in prediction of gambling behavior, including gambling.

Hypothesis 7

Similarly, Martin et al. Found that TPB determination factors were effective forecast factors for both past gambling behavior and gambling intentions. Specifically, gambling intentions were most closely related to the subjective norms of friends and family, followed by PBC. In a similar context of casino gambling, Lee has a favorable decision on casino gambling, along with the exposure of gambling media and past gambling experience with college students' casino gambling. He discovered that it was a factor. However, in Lee studies on U. S. university students, the control of the casino gambling was not a significant proximity forecast. TPB has been used to understand gambling and gambling behaviors of young adults [14, 20, 21, 22, 23]. For example, WU and Tang are the most predicted of gambling, following the attitude toward gambling, based on the attitude toward gambling, based on the attitude toward gambling, but the gambling is significantly correlated with the intention and PBC. I found that [14]. Using the Australian online survey panel, Flack and Morris have discovered that subjective norms (that are, normative beliefs) are the strongest gambling decision factors compared to other TPB variables. Gambling intention was a significant predictor of gambling frequency. In the situation in Canada, ST-PIERRE and his colleagues have significantly correlated with their attitude toward gambling and PBC over gambling, but are not correlated with the subjective norms of gambling. [21] Furthermore, the gambling frequency of Better was significantly related to gambling intentions, followed by gambling attitudes, and recognized gambling problems were more commonly predicted by the PBC, followed by gambling intentions. As a whole, ST-PIERRE and his colleagues suggested the effectiveness of TPB in prediction of gambling behavior, including gambling.

Hypothesis 8

Methods

Participants and data collection

More specifically, Wang and others argued that Wang et altogens can use the TPB framework to predict sports betting behavior. They discovered that attitude and subjective norms were important preceding factors for university students' sports betting intentions, and that PBC was a proximity to sports betting behavior. In the situation in Finland, KEKKI discovered that the intention of doing sports betting for young adults is related to the reasons for sports betting and motivation in the order of PBC, subjective norms, and sports betting. ]. In the context of Australia, Hing and others are significantly influenced by positive attitudes for sports betting participation and positive subjective norms for sports betting, especially in contact with promotion. It turned out that it was frequent [6].

Survey instrument

As has been discussed, TPB's effectiveness in explaining gambling and betting behavior is fully supported by the literature. However, it has not been relatively not paid to understand what affects the problem of college students (sports) betting behavior. Therefore, in this study, we used the TPB framework to investigate the relative importance of TPB determination factors in explaining university students' sports betting behavior (PSB).

Data analysis

According to TPB theory and literature [11, 12], the attitude toward sports betting and favorable recognition (ie, subjective norms) and positive associations in sports betting. On the other hand, it is assumed that there is a negative relationship with PBC related to sports betting. Regarding social norms related to sports betting, this study uses two components of subjective norms: (1) Expectations for important others, and (2) Friends into groups in this specific context. Motivation to follow others [22, 26]. Furthermore, the TPB framework is one of the distant factors (that is, that is, the TPB sports betting intention is to transmit the relationship between TPB's distant decisive factors (that is, norm, norm belief, compliance motivation, PBC) and PSB. PBC) was assumed that it would be directly correlated with PSB. [12] Therefore, in this study, the following hypotheses were proposed and verified (see Fig. 1):

Figure 1

Results

Descriptive statistics and correlations

Theoretical model and hypothesis

Measurement model

(H1): College students' sports betting intention is associated with favorable attitudes toward sports betting.

Structural model

(H2): College students' expectations of significant others affect their sports betting intention.

(H3): College students' motivation to comply with others affects their sports betting intention.

(H4): College students' perceived behavioral control affects their sports betting intention.

Multi-group analysis (PLS-MGA)

(H5): College students' perceived behavioral control affects their betting problem behavior.

(H6): College students' sports gambling intention affects their problem behavior.

The literature review also found inconsistencies in the relative importance of TPB determinants in explaining betting-related behavior. For example, Wang et al. argue that attitude is the most important determinant, while Kekki argues that PBC is more important in predicting college students' sports betting intention [25]. It can be argued that there are influential moderators, such as impulsive betting tendencies and previous betting experience (i. e., betting frequency), that affect the relative importance of TPB determinants in sports betting-related behaviors [27, 28].

The TPB is based on the premise that humans are usually rational and therefore make good use of available information [12]. However, there may be impulsive betting tendencies, i. e. the degree to which an individual may bet on sports unintentionally and without reflection. Similar to the concept of impulse buying [29], impulsive betting may occur when a bettor has a “predisposition to respond quickly and unplanned to internal or external stimuli without considering the negative consequences of that response” [30; p. 1784]. Thus, the relative strength of structural paths among TPB variables will vary depending on this individual tendency [28]. For example, the relationship between intention and PSB will be stronger in groups with low impulsive tendencies, since impulsive betting tendencies include unreflective betting. Additionally, attitude may be the most important distal determinant for those with low impulsivity, whereas willingness to comply may be the most important antecedent for those with high impulsivity. Thus, impulsive sports betting tendency (ISBT) appears to be a meaningful moderator in understanding the dynamics of the TPB in the context of sports betting.< .001) in comparison to the high-impulsive betting group (β = 0.34, t = 2.11, p = .035). In terms of the relative importance of the TPB distal determinants in predicting their intentions, motivation to comply (β = 0.40, t = 6.25, p < .001) was the most critical determinant, followed by the attitude (β = 0.26, t = 4.40, p < .001) and normative beliefs (β = 0.20, t = 2.26, p < .001) for the low-tendency group, while their attitude (β = 0.34, t = 4.07, p < .001) was most important for the high-tendency group, followed by motivation to comply (β = 0.28, t = 3.35, p < .001) and normative beliefs (β = 0.19, t = 2.26, p = .024).

It is logical to think that past sports gambling experience affects Better's motivation and expectations for sports betting. For the first time, the first betor and the inexperienced Better may form a betting will or determine the betting based on the commercials, advertisements of sports betting, or the word of mouth of the peers, but repeaters and experience. A bitter can be affected by the past experience of sports betting. Therefore, betors who are not very involved in betting and potential buttters are more affected by the social norms, and Betters, who are more involved, are their own attitudes (eg, cognitive effects) and betting frequency (example). It can be expected to be more affected by habitual acts). Therefore, the following hypothesis was set up (see Fig. 1).

(H7): (H7): The impulsive sports betting tendency of university students relieves the impact on the intentions and problem behavior of TPB distant factors.< .001), while it did not significantly influence the intentions of the more-experienced group (β = 0.07, t = 1.13, p = .258). The intentions had a stronger influence on problem betting behavior for the less-experienced group (β = 0.61, t = 8.36, p < .001) in comparison to the more-experienced group (β = 0.38, t = 4.79, p < .001).

Discussion

(H8): H8): A college student sports betting experience relieves the impact of the TPB distant factor on the intentions and problems of sports betting.

Data collection was performed by convenience sampling method. I asked a college student to answer the online questionnaire. The participants read the informed outlet before answering the question and answered the questionnaire without financial rewards. After excluding four incomplete respondents, a total of 311 college students participated in this study, which was 68. 2 % (n = 212) and 31. 8 % (n = 99). The average age of the participants was 20. 87 years old (SD = 2. 31). Approximately 75 % of the respondents had sports betting, and most of them were familiar with sports betting. It is logical to think that past sports gambling experience will affect the motivation and expectations of Better's sports betting. For the first time, the first betor and the inexperienced Better may form a betting will or determine the betting based on the commercials, advertisements of sports betting, or the word of mouth of the peers, but repeaters and experience. A bitter can be affected by the past experience of sports betting. Therefore, betors who are not very involved in betting and potential buttters are more affected by the social norms, and Betters, who are more involved, are their own attitudes (eg, cognitive effects) and betting frequency (example). It can be expected to be more affected by habitual acts). Therefore, the following hypothesis was set up (see Fig. 1).

(H7): (H7): The impulsive sports betting tendency of university students relieves the impact on the intentions and problem behavior of TPB distant factors.

(H8): H8): A college student sports betting experience relieves the impact of the TPB distant factor on the intentions and problems of sports betting.

Data collection was performed by convenience sampling method. I asked a college student to answer the online questionnaire. The participants read the informed outlet before answering the question and answered the questionnaire without financial rewards. After excluding four incomplete respondents, a total of 311 college students participated in this study, which was 68. 2 % (n = 212) and 31. 8 % (n = 99). The average age of the participants was 20. 87 years old (SD = 2. 31). Approximately 75 % of the respondents had sports betting, and most of them were familiar with sports betting. It is logical to think that past sports gambling experience affects Better's motivation and expectations for sports betting. For the first time, the first betor and the inexperienced Better may form a betting will or determine the betting based on the commercials, advertisements of sports betting, or the word of mouth of the peers, but repeaters and experience. A bitter can be affected by the past experience of sports betting. Therefore, betors who are not very involved in betting and potential buttters are more affected by the social norms, and Betters, who are more involved, are their own attitudes (eg, cognitive effects) and betting frequency (example). It can be expected to be more affected by habitual acts). Therefore, the following hypothesis was set up (see Fig. 1).

(H7): (H7): The impulsive sports betting tendency of university students relieves the impact on the intentions and problem behavior of TPB distant factors.

(H8): H8): A college student sports betting experience relieves the impact of the TPB distant factor on the intentions and problems of sports betting.

The survey form is based on a review of related literature, especially research related to gambling and betting using the TPB framework [12, 24, 32, 33], attitude (5 items), normative beliefs (5 items). NB; attitude (ATT; 5 items), normative beliefs (NB; 3 items), motivation for compliance (MC; 2 items), perceived action control (PBC; 2 items), sports betting intention (int; 2 items), The scale used in the past research is composed of the seven scale of the problem sports betting behavior (PSB; 4 items) and the impulsive sports betting tendency (ISBT; 3 items). The gender has been demonstrated, and it is measured using a seve n-stage Rickato scale from (1) to strong (7). (ATT), "A person who is important for me will allow me to do sports betting." "I think I can completely control sports betting" (PBC), "I'm going to continue sports betting in the near future" (int), and "Sports betting is the amount of sports betting to my family and friends. "PSB)," I often do sports betting, "(ISBT). Includes attribute information,

The main purpose of this study was to verify the theoretical framework from the viewpoint of prediction, so the data is mainly analyzed using the minimum part-sized structure equation modeling (PLS-SEM) mainly using Smartpls 3. 3. 2. It was done [34, 35]. This specific analysis method was used because this method does not require a normal distribution data by default, and can maximize the diversification of the variable. [34, 35]. Based on Hair and others guidelines [34, 35]. First, the measurement model was evaluated from the perspective of the reliability and validity of the scale. Next, the structural model was evaluated to verify the hypothesized relationship of the research model. Finally, a mult i-group SEM was adopted to verify the role of a moderator hypothesized in this study between ISBT (high ISBT and low ISBT groups) and sports gambling experience (EXP). If the main purpose of the moderator analysis is to explore the modeling effects for the entire structural model, it is better to use PLS-MGA than to test the modification effect using the inter-effects. ]. As a result, in accordance with the recommendations of Hair et al., Cluster analysis maximizes the homogeneity of the group in the cluster, but can increase the heterogeneity between groups, so the meaning of the respondents based on the experience of bed/ gambling. [34] K-average cluster analysis was used to define a su b-group (that is, a high EXP group and a low EXP group). The cluster analysis can also enhance the homogeneity of the group in the cluster while enhancing the heterogeneity between the groups.

In this study, the PLS Boot Strap Algorithm (basic correction and acceleration boot strap) using 2, 000 sub samples (basic correction and acceleration boot strap) is used to evaluate the factor load, pass coefficient, and significance level. [35, 37]. Instead of specifying a model conformity indicator when obtaining a structural model solution, PLS-SEM is mainly constituent conceptual reliability (eg, complex reliability), and composition conceptual validity (for example, explanation. It depends on different indicators, such as the average distributed and heterotrait-monotrait-ratio), and the prediction indicators (for example, a determined coefficient). [35, 37].

Data Availability

Table 1 The main purpose of the description statistics and correlation The main purpose of this study was to verify the theoretical framework from the viewpoint of the prediction, so the data is mainly the minimum square equation using Smartpls 3. 3. 2. [34, 35] was analyzed using modeling (PLS-SEM). This specific analysis method was used because this method does not require a normal distribution data by default, and can maximize the diversification of the variable. [34, 35]. Based on Hair and others guidelines [34, 35]. First, the measurement model was evaluated from the perspective of the reliability and validity of the scale. Next, the structural model was evaluated to verify the hypothesized relationship of the research model. Finally, a mult i-group SEM was adopted to verify the role of a moderator hypothesized in this study between ISBT (high ISBT and low ISBT groups) and sports gambling experience (EXP). If the main purpose of the moderator analysis is to explore the modeling effects for the entire structural model, it is better to use PLS-MGA than to test the modification effect using the inter-effects. ]. As a result, in accordance with the recommendations of Hair et al., Cluster analysis maximizes the homogeneity of the group in the cluster, but can increase the heterogeneity between groups, so the meaning of the respondents based on the experience of bed/ gambling. [34] K-average cluster analysis was used to define a su b-group (that is, a high EXP group and a low EXP group). The cluster analysis can also enhance the homogeneity of the group in the cluster while enhancing the heterogeneity between the groups.

References

In this study, the PLS Boot Strap Algorithm (basic correction and acceleration boot strap) using 2, 000 sub samples (basic correction and acceleration boot strap) is used to evaluate the factor load, pass coefficient, and significance level. [35, 37]. Instead of specifying a model conformity indicator when obtaining a structural model solution, PLS-SEM is mainly constituent conceptual reliability (eg, complex reliability), and composition conceptual validity (for example, explanation. It depends on different indicators, such as the average distributed and heterotrait-monotrait-ratio), and the prediction indicators (for example, a determined coefficient). [35, 37].
Table 1 Since the main purpose of the description statistics and correlation this research was to verify the theoretical framework from the viewpoint of the prediction, the data mainly used Smartpls 3. 3. 2 (PLS (PLS)). It was analyzed usin g-sem) [34, 35]. This specific analysis method was used because this method does not require a normal distribution data by default, and can maximize the diversification of the variable. [34, 35]. Based on Hair and others guidelines [34, 35]. First, the measurement model was evaluated from the perspective of the reliability and validity of the scale. Next, the structural model was evaluated to verify the hypothesized relationship of the research model. Finally, a mult i-group SEM was adopted to verify the role of a moderator hypothesized in this study between ISBT (high ISBT and low ISBT groups) and sports gambling experience (EXP). If the main purpose of the moderator analysis is to explore the modeling effects for the entire structural model, it is better to use PLS-MGA than to test the modification effect using the inter-effects. ]. As a result, in accordance with the recommendations of Hair et al., Cluster analysis maximizes the homogeneity of the group in the cluster, but can increase the heterogeneity between groups, so the meaning of the respondents based on the experience of bed/ gambling. [34] K-average cluster analysis was used to define a su b-group (that is, a high EXP group and a low EXP group). The cluster analysis can also enhance the homogeneity of the group in the cluster while enhancing the heterogeneity between the groups.
In this study, the PLS Boot Strap Algorithm (basic correction and acceleration boot strap) using 2, 000 sub samples (basic correction and acceleration boot strap) is used to evaluate the factor load, pass coefficient, and significance level. [35, 37]. Instead of specifying a model conformity indicator when obtaining a structural model solution, PLS-SEM is mainly constituent conceptual reliability (eg, complex reliability), and composition conceptual validity (for example, explanation. It depends on different indicators, such as the average distributed and heterotrait-monotrait-ratio), and the prediction indicators (for example, a determined coefficient). [35, 37].
Table 1 Correlation with statistics
First, the measurement model is an internal consistency reliability (that is, the alpha coefforcement and complex reliability of the cromvac), the convergence validation (that is, the factor load and average extraction distribution [AVE]), and It was evaluated from the viewpoint of (that is, heterogeneity-single-sized ratio [HTMT]). The alpha value of Cronback was in the range of 0. 65 to 0. 89, all exceeding 0. 65, the excitement of the research and research. The CR value is in the range of 0. 80 to 0. 95, significantly exceeding the 0. 70's thrilling value, indicating sufficient internal consistency reliability [34, 41, 42]. The factor load is in the range of 0. 69 to 0. 95, and the Ave value is in the range of 0. 59 to 0. 90, indicating sufficient convergence validation. Finally, the HTMT value is all lower than the 0. 85, which is a worthwhile value, and indicates the appropriate appropriate validity of the components contained in this study. [42]
Before verifying the research hypothesis, the distributed Inflation factor (VIF) value (VIF) value was examined to check the multiple c o-c o-c o-wiring of the structural model. The VIF value is within the range of 1. 01 to 2. 75, and has fallen below the recommended threshold 3. 30 [35, 43], indicating that there is no c o-wiring or common method bias. The structural model evaluation explained 60. 0%of the distributed sports gambling intentions and 40. 9%of PSB distributed, suggesting that this model has a considerable explanation ability in explaining the variable.
Table 2 Direct effects and specific indirect effects
In addition, intermediary analysis was performed in order to estimate the indirect effects of distant TPB determination factors for problem betting behavior. As reported in Table 2, a significant indirect effect on the betting problem of TPB determination indicated the presence of the intermediary. As a result, three of the four indirect routes were significant (see Table 2).
Before the mult i-group analysis, the differences between (1) low impulsive groups (n = 199) and hig h-impulsive groups (n = 112), and (2) a group of less sports betting (n). In order to examine the differences between sports betting between = 154) and many experienced groups (n = 157), an independent T-test was used. The respondents were grouped based on the impulse tendency score (4 items) and the past general backing experience and sports betting experience (4 items) using K-Means cluster analysis. Report the results in Table 3.
Table 3 Independent T-test summary
As a whole, university students with high impulsive betting trends and relatively high sports betting experience have favorable attitudes for sports betting, normative beliefs, willingness to comply with others, betting, and betting. It was shown that the level of the problem was high. It should be noted that the level of PBC was relatively the same, regardless of the group member, compared to other variables.
In order to examine the impulsive sports betting tendency adjustment effect in the research model, a mult i-group analysis approach is used based on individual impulsive trend scores (that is, high ISBT and low ISBT groups), and the pass coefficient is two groups. I evaluated whether it was different (see Table 4). Statistically, a significant difference was confirmed in the path between the intention and the problem betting behavior (p = 0. 031). More specifically, in the low impulsive betting group, the intention was strongly affected by the problem betting behavior (β = 0. 60, t = 11. 55, p.
Table 4 Summary of pass coefficient by group
Another mult i-group analysis was conducted to examine the adjustment effects of past (sports) betting experience (that is, groups with little experience and groups with many experience) (see the right column in Table 4). As a result of PLS-MGA, a statistical difference between the two groups was found in the path between normative beliefs and intentions (p = 0. 004), and the pass between intentions and problems (p = 0. 029). The normative beliefs had a stronger and significant impact on the intentions of the inexperienced groups (β = 0. 33, T = 5. 03, P)
Sports is an important factor for our culture, and in some countries, such as the United Kingdom, sports betting is a part of everyday life and a form of entertainment and lifestyle. However, Sportsbetters, especially young adult men, have a high risk of problem betting [44, 45]. Therefore, understanding what is affecting the problem of sports betting for young adults is necessary to develop a healthier sports betting culture. Overall, university students with high impulsive betting tendencies and relatively high sports betting experience have favorable attitudes for sports betting, normative beliefs, willingness to comply with others, betting, and betting. It was shown that the level of relevant potential problems was high. It should be noted that the level of PBC was relatively the same, regardless of the group member, compared to other variables.
In order to examine the impulsive sports betting tendency adjustment effect in the research model, a mult i-group analysis approach is used based on individual impulsive trend scores (that is, high ISBT and low ISBT groups), and the pass coefficient is two groups. I evaluated whether it was different (see Table 4). Statistically, a significant difference was confirmed in the path between the intention and the problem betting behavior (p = 0. 031). More specifically, in the low impulsive betting group, the intention was strongly affected by the problem betting behavior (β = 0. 60, t = 11. 55, p.
Table 4 Summary of pass coefficient by group
Another mult i-group analysis was conducted to examine the adjustment effects of past (sports) betting experience (that is, groups with little experience and groups with many experience) (see the right column in Table 4). As a result of PLS-MGA, a statistical difference between the two groups was found in the path between normative beliefs and intentions (p = 0. 004), and the pass between intentions and problems (p = 0. 029). The normative beliefs had a stronger and significant impact on the intentions of the inexperienced groups (β = 0. 33, T = 5. 03, P)
Sports is an important factor for our culture, and in some countries, such as the United Kingdom, sports betting is a part of everyday life and a form of entertainment and lifestyle. However, Sportsbetters, especially young adult men, have a high risk of problem betting [44, 45]. Therefore, understanding what is affecting the problem of sports betting for young adults is necessary to develop a healthier sports betting culture. As a whole, university students with high impulsive betting trends and relatively high sports betting experience have favorable attitudes for sports betting, normative beliefs, willingness to comply with others, betting, and betting. It was shown that the level of the problem was high. It should be noted that the level of PBC was relatively the same, regardless of the group member, compared to other variables.
In order to examine the impulsive sports betting tendency adjustment effect in the research model, a mult i-group analysis approach is used based on individual impulsive trend scores (that is, high ISBT and low ISBT groups), and the pass coefficient is two groups. I evaluated whether it was different (see Table 4). Statistically, a significant difference was confirmed in the path between the intention and the problem betting behavior (p = 0. 031). More specifically, in the low impulsive betting group, the intention was strongly affected by the problem betting behavior (β = 0. 60, t = 11. 55, p.
Table 4 Summary of pass coefficient by group
Another mult i-group analysis was conducted to examine the adjustment effects of past (sports) betting experience (that is, groups with little experience and groups with many experience) (see the right column in Table 4). As a result of PLS-MGA, a statistical difference between the two groups was found in the path between normative beliefs and intentions (p = 0. 004), and the pass between intentions and problems (p = 0. 029). The normative beliefs had a stronger and significant impact on the intentions of the inexperienced groups (β = 0. 33, T = 5. 03, P)
Sports is an important factor for our culture, and in some countries, such as the United Kingdom, sports betting is a part of everyday life and a form of entertainment and lifestyle. However, Sportsbetters, especially young adult men, are at a high risk of problem betting [44, 45]. Therefore, understanding what is affecting the issue of young adults, a young adult, is necessary to develop a healthier sports betting culture.
In this study, we used the TPB framework to examine the preceding factors, intermediary factors, and adjustment factors of university students' sports betting problems. As a result, the distal TPB variable contributed significantly to the explanation of the close TPB variables (intention), and the intention of university students to sports betting, and the PBC is effective in determining the (potential) problem sports betting behavior. It was suggested that it was. Furthermore, this study suggested that impulsive betting trends and past sports betting experience could be a meaningful adjustment factor in understanding the degree of TPB determination factors that predict sports betting behavior. The results of this study supported the usefulness of TPB and extension variables in the context of university students in sports betting. Please refer to Figure 2 for the summary of this research.
Figure 2
Final model using pass coefficient
The intention to implement sports betting was most closely related to university students' attitudes for sports betting, motivation to comply with others, and norms. Positive attitudes for sports betting, the strength of normative awareness, and the growing motivation to follow others will increase the intention to sports betting. However, unlike our expectations, PBC had no direct relationship with the intention of sports betting. Not everyone with a highly intention of sports betting does not experience betting / gambling problems, but it is highly likely that college students who are highly willing to betting and often have actual betting behavior will experience bettin g-related problems. You can think of it. Therefore, understanding the intentions of sports betting and the factor in the betting problem is considered to be one of the important issues for developing responsible betting culture and strategy [14, 22, 23, 45. ]. In this study, we used the TPB framework to examine the preceding factors, intermediary factors, and adjustment factors for university students' sports betting problems. As a result, the distal TPB variable contributed significantly to the explanation of the close TPB variables (intention), and the intention of university students to sports betting, and the PBC is effective in determining the (potential) problem sports betting behavior. It was suggested that it was. Furthermore, this study suggested that impulsive betting trends and past sports betting experience could be a meaningful adjustment factor in understanding the degree of TPB determination factors that predict sports betting behavior. The results of this study supported the usefulness of TPB and extension variables in the context of university students in sports betting. Please refer to Figure 2 for the summary of this research.
Figure 2
Final model using pass coefficient
The intention to implement sports betting was most closely related to university students' attitudes for sports betting, motivation to comply with others, and norms. Positive attitudes for sports betting, the strength of normative awareness, and the growing motivation to follow others will increase the intention to sports betting. However, unlike our expectations, PBC had no direct relationship with the intention of sports betting. Not everyone with a highly intention of sports betting does not experience betting / gambling problems, but it is highly likely that college students who are highly willing to betting and often have actual betting behavior will experience bettin g-related problems. You can think of it. Therefore, understanding the intentions of sports betting and the factor in the betting problem is considered to be one of the important issues for developing responsible betting culture and strategy [14, 22, 23, 45. ]. In this study, we used the TPB framework to examine the preceding factors, intermediary factors, and adjustment factors of university students' sports betting problems. As a result, the distal TPB variable contributed significantly to the explanation of the close TPB variables (intention), and the intention of university students to sports betting, and the PBC is effective in determining the (potential) problem sports betting behavior. It was suggested that it was. Furthermore, this study suggested that impulsive betting trends and past sports betting experience could be a meaningful adjustment factor in understanding the degree of TPB determination factors that predict sports betting behavior. The results of this study supported the usefulness of TPB and extension variables in the context of university students in sports betting. Please refer to Figure 2 for the summary of this research.
Figure 2
Final model using pass coefficient
The intention to implement sports betting was most closely related to university students' attitudes for sports betting, motivation to comply with others, and norms. Positive attitudes for sports betting, the strength of normative awareness, and the growing motivation to follow others will increase the intention to sports betting. However, unlike our expectations, PBC had no direct relationship with the intention of sports betting. Not everyone with a highly intention of sports betting does not experience betting / gambling problems, but it is highly likely that college students who are highly willing to betting and often have actual betting behavior will experience bettin g-related problems. You can think of it. Therefore, understanding the intentions of sports betting and the factor in the betting problem is considered to be one of the important issues for developing responsible betting culture and strategy [14, 22, 23, 45. ].
It matched the literature [8, 45, 46], suggesting that the attitude toward sports betting is an important factor in betting. Generally, people take a negative attitude toward betting, as they can have harmful results. [44] However, the positive image and establishment of sports in society tend to take a more friendly attitude toward sports betting. Young adults are accustomed to professional sports and are identified compared to other age groups, so they win a relatively positive attitude toward sports betting (for example, sports betting lives life). There is a tendency to overestimate possibilities (that is, excessive positive cognitive attitude). For example, SEALs and others who are favorable and tolerant of sports, that is, sports fans who recognize that sports betting are harmless, general, and part of sports tend to bet on sports. [45] Thus, health promotion and regulatory agencies need to develop better educational campaigns to improve knowledge and the harmful consequences of pathological sports betting. It is also necessary to reconsider how the media treats information about sports betting, taking into account the influence of the media that forms a perception of sports betting. It matches the literature [8, 45, 46], suggesting that the attitude toward sports betting is an important decision factor in betting. Generally, people take a negative attitude toward betting, as they can have harmful results. [44] However, the positive image and establishment of sports in society tend to take a more friendly attitude toward sports betting. Young adults are accustomed to professional sports and are identified compared to other age groups, so they win a relatively positive attitude toward sports betting (for example, sports betting lives life). There is a tendency to overestimate possibilities (that is, excessive positive cognitive attitude). For example, SEALs and others who are favorable and tolerant of sports, that is, sports fans who recognize that sports betting are harmless, general, and part of sports tend to bet on sports. [45] Thus, health promotion and regulatory agencies need to develop better educational campaigns to improve knowledge and the harmful consequences of pathological sports betting. It is also necessary to reconsider how the media treats information about sports betting, taking into account the influence of the media that forms a perception of sports betting. It matched the literature [8, 45, 46], suggesting that the attitude toward sports betting is an important factor in betting. Generally, people take a negative attitude toward betting, as they can have harmful results. [44] However, the positive image and establishment of sports in society tend to take a more friendly attitude toward sports betting. Young adults are accustomed to professional sports and are identified compared to other age groups, so they win a relatively positive attitude toward sports betting (for example, sports betting lives life). There is a tendency to overestimate possibilities (that is, excessive positive cognitive attitude). For example, SEALs and others who are favorable and tolerant of sports, that is, sports fans who recognize that sports betting are harmless, general, and part of sports tend to bet on sports. [45] Thus, health promotion and regulatory agencies need to develop better educational campaigns to improve knowledge and the harmful consequences of pathological sports betting. It is also necessary to reconsider how the media treats information about sports betting, taking into account the influence of the media that forms a perception of sports betting.
The significant determinants of sports betting behavior and potential betting problems among college students were compliance motivation and normative consciousness toward sports betting. Compared to older adults, college students are more susceptible to peer group influence. Gordon et al. used the concept of lifestyle consumption community (LCC) in explaining sports betting behavior among young adult non-pathological gamblers [47]. Young male adults are more likely to have a stronger and more diverse LCC due to their active lifestyle, and therefore are more likely to be influenced by LCC in their (continuous) participation in sports betting. They also tend to overestimate how much others are betting, and thus affirm the activity associated with betting. Seal et al.'s study also found that sports bettors, compared to non-bettors and non-sports bettors, may have a false consensus (biased social norms) about betting participation in general, because they believe that most people in society bet on sports [45]. Sports bettors believe that their family and friends are supportive of their sports betting behavior. In particular, sports bettors are surrounded by a group of friends who bet on sports and regularly discuss sports betting [12, 23, 47]. Therefore, preventive efforts should focus on changing college students' misperceptions about sports betting and how to effectively manage peer pressure for sports betting [48]. Strong social support (i. e., social norms) is a key determinant of college students' sports betting behavior and potential betting problems was compliance motivation to others and normative consciousness about sports betting. Compared to older adults, college students are more likely to be influenced by their peer group. Gordon et al. used the concept of lifestyle consumption community (LCC) when explaining the sports betting behavior of young adult non-pathological gamblers [47]. Young male adults are more likely to have a stronger and more diverse LCC due to their active lifestyle, and therefore are more likely to be influenced by LCC in their (continuous) participation in sports betting. They also tend to overestimate how much others are betting and affirm the activity associated with betting. A study by Seal et al. also found that compared to non-bettors and non-sports bettors, sports bettors may have a false consensus (biased social norms) about betting participation in general because they believe that most people in society bet on sports [45]. Sports bettors believe that their family and friends support their sports betting behavior. In particular, sports bettors are surrounded by a group of friends who bet on sports and regularly discuss sports betting with them [12, 23, 47]. Therefore, preventive efforts should focus on changing college students' false perceptions about sports betting and how to effectively manage peer pressure for sports betting [48]. Strong social support (i. e., social norms) may be a factor in college students' sports betting behavior and potential betting problems. Compliance motivation for others and normative consciousness about sports betting were significant determinants of college students' sports betting behavior and potential betting problems. Compared to older adults, college students are more susceptible to peer group influence. Gordon et al. used the concept of lifestyle consumption community (LCC) to explain the sports betting behavior of young adult non-pathological gamblers [47]. Young male adults are more likely to have a stronger and more diverse LCC due to their active lifestyles, and therefore are more likely to be influenced by LCC in their (continuous) participation in sports betting. They also tend to overestimate how much others are betting, and thus affirm the activity associated with betting. Seal et al.'s study also found that sports bettors, compared to non-bettors and non-sports bettors, may have a false consensus (biased social norms) about betting participation in general, as they believe that most people in society bet on sports [45]. Sports bettors believe that their family and friends are supportive of their sports betting behavior. In particular, sports bettors are surrounded by a group of friends who bet on sports and regularly discuss sports betting with them [12, 23, 47]. Therefore, preventive efforts should focus on changing college students’ misconceptions about sports betting and how to effectively manage peer pressure to bet on sports [48]. Strong social support (i. e., social norms) may be a factor in determining whether students are willing to bet on sports.
College students with low PBCs on resistance to sports betting are more likely to sports betting, and are more likely to take problems. [12] In this study, PBC could not find a significant impact on intention, but hypothesis showed a negative relationship with college students' problems. Regarding PBC, one of the major issues is that university students overestimate their ability to participate and control the results. Overlating the possibility of winning is one of the most important prediction factors of the problem betting. Therefore, it is necessary to make an intervention effort to ensure that Better does not overestimate the winning rate [51] so that betting behavior can be controlled. Betting in drunkenness (such as a drunken or hig h-conditioned state) is harmful, especially for young people aged 18 to 24, leading to risk take, waste, and worsen human relationships. Therefore, educational institutions and health promotion agencies need to educate university students to control sports betting and to educate the harmful results brought about drunk.
The impulsive sports betting tendency of university students and past betting experience played a moderator in the relationship between betting intention and program betting. The relationship between intentions and PSB was stronger in lo w-impulsive groups and experienced groups. Betting intentions are the most important factors that predict the potential of sports betting and program betting, but to understand the problem betting of college students, customary acts, character variables (such as pursuit of senses), material consumption, Other potential decision factors and moderators, such as impulsivity, also need to take into account at the same time. Youth people tend to pursue losing, especially when betting online, tend to bet on more than margin. [53] In recent years, young people have been betting e-sports online, as e-sports betting services have increased rapidly. Onlineberg has a significant relevance to impulsive betting and problem betting than conventional fac e-t o-face betting, so in future studies, sports betting categories (that is, for conventional betting and e-sports to sports. You need to check the effects of).
The theoretical framework of this study was the TPB, given its usefulness and applicability in understanding betting-related behaviors. Although this study included extended variables, especially moderators, to understand sports betting behaviors among college students, future studies should consider other potentially meaningful constructs and variables, such as personality traits and substance consumption [22, 26].
For future research, several limitations of this study should be noted. First, this study utilized a cross-sectional research design with a convenience sampling method. Also, different states in the United States have different legal guidelines regarding sports betting [15]. Therefore, the results of this study may not be generalizable to college populations in other countries. Second, although all the scales used in this study were reliable and valid, one of the scales used in this study had a lower reliability value than desired (i. e., Cronbach's alpha was 0. 65 instead of 0. 70). Future studies should consider using more reliable scales found in the literature. Overall, although there are some limitations, the model proposed in this study can be used as a solid basis for future research on sports betting, as it incorporates non-volatile variables (e. g., impulsive betting tendencies) while using the TPB as a conceptual framework. As a result, this study can contribute to the development of better education and intervention programs for sports betting and problem betting by improving our understanding of college bettors.
The datasets generated and analyzed in this study are not publicly available due to confidentiality and privacy concerns, but are available from the corresponding author upon reasonable request.
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Acknowledgements

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